scholarly journals How do the surface energy fluxes change when a more realistic land cover is included in the WRF model? An evaluation using BLLAST data

2021 ◽  
Author(s):  
Carlos Román-Cascón ◽  
Marie Lothon ◽  
Fabienne Lohou ◽  
Oscar Hartogensis ◽  
Jordi Vila-Guerau de Arellano ◽  
...  
Keyword(s):  
Surface Energy ◽  
Land Cover ◽  
Land Surface ◽  
Wrf Model ◽  
Common Interest ◽  
Vegetation Types ◽  
Energy Fluxes ◽  
Surface Parameters ◽  
The Real ◽  
Surface Energy Fluxes

<p>Ideally, numerical weather prediction (NWP) and climate models should include a proper representation of the land surface to correctly simulate the surface energy fluxes and, ultimately, provide successful forecasts of atmospheric variables of common interest for the humans (2-m temperature, 10-m wind speed, relative humidity, etc.). However, in some cases, the issues begin in the first link of this chain, i.e., the surface characteristics included in the model do not represent appropriately the real surface ones in certain areas.</p><p>This work investigates how the simulated surface energy fluxes change when the land cover (LC) of an area is improved using a more realistic and higher-resolution dataset. We evaluate the Weather Research and Forecasting (WRF) model simulating a fair-weather day in a heterogeneous area of southern France. Firstly, we use the default LC database in WRF, which differed significantly from the real LC in the area. Secondly, we improve the LC representation of the studied area using a more realistic 1-km dataset prepared by the CESBIO research laboratory. The simulated fluxes were evaluated in a 19x19 km area with gridded area-averaged fluxes computed using measurements from five eddy-covariance towers deployed over different vegetation types during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The evaluation is done using four land-surface models (LSM) available in WRF (Noah, Noah-MP, CLM4 and RUC).</p><p>The results differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within each grid cell. The simulated fluxes improved when a more realistic LC dataset is used except for some LSMs that considered extreme surface parameters for some LC categories (coniferous forest and urban surfaces). Therefore, our findings encourage to check (and improve if needed) the surface representation in the model over the area of analysis, as well as to update surface parameters for some vegetation types.</p>

scholarly journals Remotely sensed land-surface energy fluxes at sub-field scale in heterogeneous agricultural landscape and coniferous plantation

2014 ◽  
Vol 11 (18) ◽  
pp. 5021-5046 ◽  
Author(s):  
R. Guzinski ◽  
H. Nieto ◽  
R. Jensen ◽  
G. Mendiguren
Keyword(s):  
Surface Energy ◽  
Spatial Resolution ◽  
Land Surface ◽  
Agricultural Landscape ◽  
Remotely Sensed ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Coniferous Plantation ◽  
Polar Orbiting Satellite ◽  
Agricultural Site

Abstract. In this study we evaluate a methodology for disaggregating land surface energy fluxes estimated with the Two-Source Energy Balance (TSEB)-based Dual-Temperature Difference (DTD) model which uses day and night polar orbiting satellite observations of land surface temperature (LST) as a remotely sensed input. The DTD model is run with MODIS input data at a spatial resolution of around 1 km while the disaggregation uses Landsat observations to produce fluxes at a nominal spatial resolution of 30 m. The higher-resolution modelled fluxes can be directly compared against eddy covariance (EC)-based flux tower measurements to ensure more accurate model validation and also provide a better visualization of the fluxes' spatial patterns in heterogeneous areas allowing for development of, for example, more efficient irrigation practices. The disaggregation technique is evaluated in an area covered by the Danish Hydrological Observatory (HOBE), in the west of the Jutland peninsula, and the modelled fluxes are compared against measurements from two flux towers: the first one in a heterogeneous agricultural landscape and the second one in a homogeneous conifer plantation. The results indicate that the coarse-resolution DTD fluxes disaggregated at Landsat scale have greatly improved accuracy as compared to high-resolution fluxes derived directly with Landsat data without the disaggregation. At the agricultural site the disaggregated fluxes display small bias and very high correlation (r ≈ 0.95) with EC-based measurements, while at the plantation site the results are encouraging but still with significant errors. In addition, we introduce a~modification to the DTD model by replacing the "parallel" configuration of the resistances to sensible heat exchange by the "series" configuration. The latter takes into account the in-canopy air temperature and substantially improves the accuracy of the DTD model.

Using Spatial Eddy Covariance to Investigate Energy Balance Closure over a Heterogeneous Ecosystem

2020 ◽  
Author(s):  
Brian Butterworth ◽  
Ankur Desai ◽  
Sreenath Paleri ◽  
Stefan Metzger ◽  
David Durden ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Energy Balance ◽  
Surface Energy ◽  
Atmospheric Boundary Layer ◽  
Eddy Covariance ◽  
Land Surface ◽  
Surface Heterogeneity ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Land Surface Heterogeneity

<p>Land surface heterogeneity influences patterns of sensible and latent heat flux, which in turn affect processes in the atmospheric boundary layer. However, gridded atmospheric models often fail to incorporate the influence of land surface heterogeneity due to differences between the temporal and spatial scales of models compared to the local, sub-grid processes. Improving models requires the scaling of surface flux measurements; a process made difficult by the fact that surface measurements usually find an imbalance in the energy budget.</p><p>The Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD19) was an observational experiment designed to investigate how the atmospheric boundary layer responds to scales of spatial heterogeneity in surface-atmosphere heat and water exchanges. The campaign was conducted from June – October 2019, measuring surface energy fluxes over a heterogeneous forest ecosystem as fluxes transitioned from latent heat-dominated summer through sensible heat-dominated fall. Observations were made by ground, airborne, and satellite platforms within the 10 x 10 km study region, which was chosen to match the scale of a typical model grid cell. The spatial distribution of energy fluxes was observed by an array of 20 eddy covariance towers and a low-flying aircraft. Mesoscale atmospheric properties were measured by a suite of LiDAR and sounding instruments, measuring winds, water vapor, temperature, and boundary layer development. Plant phenology was measured in-situ and mapped remotely using hyperspectral imaging.</p><p>The dense set of multi-scale observations of land-atmosphere exchange collected during the CHEESEHEAD field campaign permits combining the spatial and temporal distribution of energy fluxes with mesoscale surface and atmospheric properties. This provides an unprecedented data foundation to evaluate theoretical explanations of energy balance non-closure, as well as to evaluate methods for scaling surface energy fluxes for improved model-data comparison. Here we show how fluxes calculated using a spatial eddy covariance technique across the 20-tower network compare to those of standard temporal eddy covariance fluxes in order to characterize of the spatial representativeness of single tower eddy covariance measurements. Additionally, we show how spatial EC fluxes can be used to better understand the energy balance over heterogeneous ecosystems.</p>

scholarly journals Aerosol effects on global land surface energy fluxes during 2003-2010

2014 ◽  
Vol 41 (22) ◽  
pp. 7875-7881 ◽  
Author(s):  
Shaoqing Liu ◽  
Min Chen ◽  
Qianlai Zhuang
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Global Land ◽  
Aerosol Effects

scholarly journals The topographic control on land surface energy fluxes: A statistical approach to bias correction

2020 ◽  
Vol 584 ◽  
pp. 124669
Author(s):  
Alessandra Trevisan ◽  
Victor Venema ◽  
Stefan Kollet ◽  
Mostaquimur Rahman
Keyword(s):  
Surface Energy ◽  
Bias Correction ◽  
Land Surface ◽  
Statistical Approach ◽  
Energy Fluxes ◽  
Surface Energy Fluxes
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